Gas sensors are disclosed having an on-board, low-power data processor that uses multivariable gas classification and/or gas quantitation models to perform on-board data processing to resolve two or more gases in a fluid sample. To reduce computational complexity, the gas sensor utilizes low-power-consumption multivariable data analysis algorithms, inputs from available on-board sensors of ambient conditions, inputs representing contextual data, and/or excitation responses of a gas sensing material to select suitable gas classification and/or gas quantitation models. The data processor can then utilize these gas classification and quantitation models, in combination with measured dielectric responses of a gas sensing material of the gas sensor, to determine classifications and/or concentrations of two or more gases in a fluid sample, while consuming substantially less power than would be consumed if a global comprehensive model were used instead. Thus, the data processor is utilized for linear, nonlinear, and non-monotonic multivariate regressions.
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July 7, 2022
May 7, 2024
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